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Dance Revolution: Long-Term Dance Generation with Music via Curriculum Learning
In this paper, we formalize the music-conditioned dance generation as a sequence-to-sequence learning problem and devise a novel seq2seq architecture to efficiently process long sequences of music features and capture the fine-grained correspondence between music and dance.
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How Sequence-to-Sequence Models Perceive Language Styles?
Style is ubiquitous in our daily language uses, while what is language style to learning machines?
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